共查询到16条相似文献,搜索用时 156 毫秒
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基于多元回归的调节效应分析 总被引:2,自引:0,他引:2
在心理学和其他社科研究领域,大量实证研究建立调节模型,以分析自变量对因变量关系的影响机制,但在基于多元回归的调节效应分析实践中仍存在不足。我们回顾了均值中心化在基于多元回归的调节效应分析中的作用,均值中心化不影响乘积项(即调节效应)的检验,仅对一阶项(即主效应)的检验有影响。讨论了简单斜率的检验方法,建议在调节变量为连续变量时,使用Johnson-Neyman法进行简单斜率检验;在调节变量为类别变量或研究者对某个调节变量值感兴趣时,使用选点法。并用一个实际例子演示如何进行调节效应分析。随后展望了调节效应检验的拓展方向。 相似文献
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目前调节效应检验主要是基于截面数据, 本文讨论纵向(追踪)数据的调节效应分析。如果自变量X和因变量Y有纵向数据, 调节效应可分为三类:调节变量Z不随时间变化、Z随时间变化、调节变量从自变量或因变量中产生。评介了基于多层模型、多层结构方程模型、交叉滞后模型和潜变量增长模型的纵向数据的多种调节效应分析方法。调节效应的分解和潜调节结构方程法的使用是纵向数据的调节效应分析的两大特点。对基于四类模型的调节效应分析方法进行综合比较后, 总结出一个纵向数据的调节效应分析流程。随后用实际例子演示如何进行纵向数据的调节效应分析, 并给出相应的Mplus程序。随后展望了纵向数据的调节效应分析的拓展方向, 例如基于动态结构方程模型的密集追踪数据的调节效应分析。 相似文献
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基于结构方程模型的有调节的中介效应分析 总被引:1,自引:0,他引:1
有调节的中介模型是中介过程受到调节变量影响的模型。指出了目前有调节的中介效应分析普遍存在的问题:当前有调节的中介效应检验大多使用多元线性回归分析,忽略了测量误差;而基于结构方程模型(SEM)的有调节的中介效应分析需要产生乘积指标,又会面临乘积指标生成和乘积项非正态分布的问题。在简介潜调节结构方程(LMS)方法后,建议使用LMS方法得到偏差校正的bootstrap置信区间来进行基于SEM的有调节的中介效应分析。总结出一个有调节的中介SEM分析流程,并有示例和相应的Mplus程序。文末展望了LMS和有调节的中介模型的发展方向。 相似文献
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类别变量的中介效应分析 总被引:4,自引:0,他引:4
在心理学和其他社科研究领域,研究者能熟练地进行连续变量的中介效应分析,但面对自变量、中介变量或(和)因变量为类别变量的中介效应分析,研究者往往束手无策。在阐述类别自变量中介分析方法的基础上,我们建议使用整体和相对中介相结合的类别自变量中介分析方法,并给出了分析流程。以二分因变量为例,讨论了中介变量或(和)因变量为类别变量的中介分析方法的发展过程(即尺度统一的过程),建议通过检验Za×Zb的显著性来判断中介效应的显著性。用二个实际例子演示如何进行类别变量的中介效应分析。最后展望了类别变量的中介效应分析研究的拓展方向。 相似文献
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类别变量在心理学和其他社科研究领域经常遇到,当自变量或调节变量为类别变量时,应当如何分析调节效应呢?详述了多类别变量的被试间设计和两水平被试内设计(因变量重复测量2次)的调节效应分析方法,并给出了分析流程。先进行调节效应的显著性检验,后用选点法或Johnson-Neyman法进行简单斜率检验。多类别变量被试间设计的简单斜率检验是先进行整体检验,后进行配对检验。用两个实际例子演示如何进行类别变量的调节效应分析,最后展望了两类设计的类别变量的调节研究的拓展方向,例如更复杂的类别变量的调节模型等。 相似文献
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传统的有中介的调节(mediated moderation, meMO)模型关于误差方差齐性的假设经常被违背, 应用研究中也缺乏测量meMO效应大小的指标。对于单层数据, 本文借助于两层建模的思想, 提出了一种可用于处理方差非齐性的两层有中介的调节(2meMO)模型; 给出了用于测量meMO分析中总调节效应、直接调节效应和有中介调节效应大小的效应量。通过Monte Carlo模拟研究, 比较了meMO和2meMO模型在参数和效应量估计上的表现。并通过实际案例解释了2meMO模型的应用以及效应量的计算和解释。 相似文献
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Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model. 相似文献
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多层中介和多层调节效应分析在社科领域已常有应用,但如果将多层中介和调节整合在一起,可以产生2(多层中介类型)×2(调节变量的层次)×3(调节的中介路径)共12种有调节的多层中介模型。面对有调节的多层中介效应分析,研究者往往束手无策。详述了基于多层线性模型的12种有调节的多层中介的分析方法和基于多层结构方程模型的4类有调节的多层中介分析方法,包括正交分割法,随机系数预测法,潜调节结构方程法和贝叶斯合理值法。这四类方法的核心议题在于如何处理潜调节项。当样本量足够大时,建议选择潜调节结构方程法;当样本量不足时,建议选择贝叶斯合理值法。随后用一个实际例子演示如何进行有调节的多层中介效应分析并有相应的Mplus程序。最后展望了有调节的多层中介效应分析研究的拓展方向。 相似文献
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Gwowen Shieh 《Behavior research methods》2009,41(1):61-74
Moderated multiple regression (MMR) has been widely used to investigate the interaction or moderating effects of a categorical
moderator across a variety of subdisciplines in the behavioral and social sciences. In view of the frequent violation of the
homogeneity of error variance assumption in MMR applications, the weighted least squares (WLS) approach has been proposed
as one of the alternatives to the ordinary least squares method for the detection of the interaction effect between a dichotomous
moderator and a continuous predictor. Although the existing result is informative in assuring the statistical accuracy and
computational ease of the WLS-based method, no explicit algebraic formulation and underlying distributional details are available.
This article aims to delineate the fundamental properties of the WLS test in connection with the well-known Welch procedure
for regression slope homogeneity under error variance heterogeneity. With elaborately systematic derivation and analytic assessment,
it is shown that the notion of WLS is implicitly embedded in the Welch approach. More importantly, extensive simulation study
is conducted to demonstrate the conditions in which the Welch test will substantially outperform the WLS method; they may
yield different conclusions. Welch’s solution to the Behrens-Fisher problem is so entrenched that the use of its direct extension
within the linear regression framework can arguably be recommended. In order to facilitate the application of Welch’s procedure,
the SAS and R computing algorithms are presented. The study contributes to the understanding of methodological variants for
detecting the effect of a dichotomous moderator in the context of moderated multiple regression. Supplemental materials for
this article may be downloaded from brm.psychonomic-journals.org/content/supplemental. 相似文献
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Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis 总被引:5,自引:0,他引:5
Studies that combine moderation and mediation are prevalent in basic and applied psychology research. Typically, these studies are framed in terms of moderated mediation or mediated moderation, both of which involve similar analytical approaches. Unfortunately, these approaches have important shortcomings that conceal the nature of the moderated and the mediated effects under investigation. This article presents a general analytical framework for combining moderation and mediation that integrates moderated regression analysis and path analysis. This framework clarifies how moderator variables influence the paths that constitute the direct, indirect, and total effects of mediated models. The authors empirically illustrate this framework and give step-by-step instructions for estimation and interpretation. They summarize the advantages of their framework over current approaches, explain how it subsumes moderated mediation and mediated moderation, and describe how it can accommodate additional moderator and mediator variables, curvilinear relationships, and structural equation models with latent variables. 相似文献
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Victor Bissonnette William Ickes Ira Bernstein Eric Knowles 《Journal of personality》1990,58(3):567-587
ABSTRACT Personality moderating variables act to qualify the relationship between a personality trait measure and a relevant behavioral criterion. Two data analytic techniques that can be used to test for significant moderating effects are the "median split" (MS) approach and the "moderated multiple regression" (MMR) approach. The goals of the present research were ( a ) to apply the MS approach to computer-simulated data in which the moderator and trait extremity are confounded, to determine the extent of artifact, and ( b ) to compare the performance (Type I and Type II error rates) of the two approaches when applied to confounded and nonconfounded data. It was found that when the MS approach was applied to confounded data in which no real moderating effect existed, this approach produced an alarming rate of apparent, but spurious, moderating effects. When the MMR approach was applied to the same data, the rate of spurious effects was reduced to that expected by chance. When both approaches were applied to simulated data which contained genuine moderating effects, the MMR approach consistently resulted in more correct detections of these effects than the MS approach. We conclude that researchers should always employ the MMR rather than the MS approach when testing for personality moderator variable effects. 相似文献